1. Field
The present teachings generally relate to nucleic acid analysis, and in various embodiments, to a system and methods for detecting and identifying heterozygous indel mutations.
2. Description of the Related Art
Allelic variations comprising differences in the genomic sequence between same-species organisms have be found to occur with relatively high frequency. For example, allelic variations referred to as single nucleotide polymorphisms (SNPs) are estimated to occur approximately one out of every three hundred basepairs, translating to an estimated total of over ten million SNPs in the human genome. Evaluating the frequency and distribution of allelic variations may be useful in identification of disease related loci and may serve as a diagnostic tool for determining genetic susceptibility to a variety of diseases including; hereditary thrombophilia, cystic fibrosis, and cancer. Existing methods for allelic variation identification generally necessitate the sequencing of large numbers of nucleotide fragments or strands generating vast amounts of data that must be sifted through to identify significant base differences. Using conventional data analysis approaches, difficulties often arise in identifying the presence and nature of a particular sequence variation. For example, differences between two alleles may result from insertion, deletion, or substitution of one or more bases. Identifying and distinguishing between these types of variations in an automated manner through computer-based analysis further presents problems in terms of accuracy and reliability. In this regard, there is a need for more robust analytical approaches that may be adapted for use with high-throughput sequencing methods to identify allelic variations with an improved degree of reliability and accuracy.